AI Summit London 2024: Key Events

Like digital transformation, AI adoption and implementation are challenging and require much more than just technology to succeed. Below are some of the insights and recommendations VML Intelligence gathered from this year’s summit.

Create the future of AI: Don’t build for what AI can do now, but for what it can do in the future, says Colin Jarvis of OpenAI. Developments are changing so quickly that by the time you build something, the field is already in motion.

Artificial intelligence alone will not be able to distinguish between: AI is quickly becoming the order of the day, and the technology itself won’t stand out. The user experience, proprietary data and services you bring to it will provide the difference, Jarvis said.

Balancing human control and automation in user experiences: Speakers pointed to the need for AI to provide human expertise in certain cases where processes or decision-making are more complex or where greater empathy is required. Tim Bond, deputy director of media at IPSOS, joked that AI is “an exoskeleton that needs a human at its heart, otherwise it’s just a bag of bones.”

Don’t chase the latest news, have clear goals: Sid Chaudhary and Sawat Choudhury of Mars Wrigley’s digital commerce division suggested that marketers can often be guilty of “chasing the shiny toy” instead of prioritizing results. Fractional CTO Adil Asif said that many AI implementation projects fail due to a lack of clear goals or poor decision-making. It’s important to remember that AI is not software, it’s not iterative or sequential, he said, “it’s closer to discovery than to development, and that’s how we as business leaders should view it.”

Consider unexpected effects: Daniel Hulme, WPP’s chief AI officer, warned that AI won’t solve all problems. “Just because you can doesn’t mean you should,” agreed Sara Chapman of Adam & Eve. Both suggested it was important to consider the side effects of AI — both in the supply chain and within teams. As Chapman notes, “simple tasks are what we tend to give to younger workers,” while also offering a respite from intense work. Are we looking to automate All is it boring?

Make it ethical, transparent and responsible: As companies create task forces, develop key policies and appoint boards to oversee AI implementation, responsible AI is becoming more common, but there is still a long way to go. Transparency should be a key point, said Daniel Hulme, who noted that “AI is not explainable at the moment” and that intentions need to be made easier to see. Emma di Orio, global head of data privacy at Diageo, argued that data privacy should be seen as a business enabler, a path to trust and competitive advantage. The final word goes to Alyssa Lefaivre Škopac of the Responsible AI Institute, who agreed that “trustworthy AI will win in the marketplace.”